IJIEEE Journal

Paper Title - Vehicle Speed Determination using HMM

Abstract
This paper presents an application of computer vision methods for traffic vehicle tracking and speed detection.
The application is utilizing background subtraction, object detection, feature selection and then object tracking. These
methods combined together gives functional capabilities to the system to initiate automated vehicle tracking and to
determine their speeds. To find the speed of vehicle in a high road we introduce a statistical probability model namely
Hidden Markov Model (HMM) .In this method we will train the HMM using cars videos with speeds within the specified
range which we want to consider. After training we test the car speeds on the trained HMM, if car in the video have a speed
within the specified range the HMM will give a high probability value and if it is less or more than the specified range it will
give a low probability value.
Keywords - Hidden Markov Model (HMM), Feature Extraction, Blob Identification, Object Detection, Object Tracking,
Kalman Filter.